Skip to main content
Log in

Repulsive Function in Potential Field Based Control with Algorithm for Safer Avoidance

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

In this article, a collision avoidance scheme based on potential functions is proposed. The first part of the paper is intended to establish the equations of the dynamic model of the vehicle, potential attractive functions and nested saturation controller. In the second part, the repulsive scheme is developed. Along with the repulsive scheme, the controller constants are optimized, in order to perform a safer avoidance maneuver. The advantages of the proposed repulsive schemes compared with a conventional repulsive function are demonstrated by simulations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Maria Carmela De, G., Jadbabaie, A.: Formation control for a cooperative multy-agent system using decentralized navigation functions. In Proceedings of the 2006 American Control Conference, June 14-16 (2006)

  2. Yi, L., Lee, H.-H.: Decentralized formation control and obstacle avoidance for multiple robots with nonholonomic constraint. In: Proceedings of the 2006 American Control Conference, pages 5596–5601, June 14-16 (2006)

  3. Paul, T., Krogstad, T. R., Gravdahl, J. T.: Uav formation flight using 3d potential field. In: 16th Mediterranean Conference on Control and Automation, pp. 1240–1245, June 25-27 (2008)

  4. Xue, D., Yao, J., Chen, G., Yu, Y.-L.: Formation control of networked multi-agent systems. IET Control Theory Appl. 4(10), 2168–2176 (2010)

    Article  MathSciNet  Google Scholar 

  5. Vadakkepat, P., Tan, K. C., Ming-Liang, W.: Evolutionary artificial potential fields and their application in real time robot path planning. In: Congress on Evolutionary Computation, Vol. 1, pp 256–263 (2000)

  6. Valbuena, L., Tanner, H. G.: Hybrid potential field based control of differential drive mobile robots. J. Intell. Robot. Syst. 68(3-4), 307–322 (2012)

    Article  MATH  Google Scholar 

  7. Cruz, G. C. S., Encarnação, P.M.M.: Obstacle avoidance for unmanned aerial vehicles. J. Intell. Robot. Syst. 65(1-4), 203–217 (2012)

    Article  Google Scholar 

  8. Jean-Claude, L.: Robot Motion Planning. Kluwer Academic Publishers, MA, USA (1991)

    Google Scholar 

  9. Tang, Q., Yi, S., Chengyu, H., Zeng, J.: Multi-swarm cooperation optimization for multi-modal functions in repulsive potential field. In: Fourth International Workshop on Advanced Computational Intelligence, pp. 70–74, Oct. 19-21 (2011)

  10. Leng-Feng, L.: Decentralized motion planning with an artificial potential framework (apf) for cooperative payload transport by multi-robot collectives. Master?s thesis, Faculty of the Graduate School of the State University of New York (2004)

  11. Ge, S. S., Cui, Y. J.: New potential functions for mobile robot path planning. IEEE Trans. Robot. Autom. 16(5), 615–620 (2000)

    Article  Google Scholar 

  12. Shi, P., Zhao, Y.: Global path planning for mobile robot based on improved artificial potential function. In International Conference on Automation and Logistics, pp 1900–1904 (2009)

  13. Jia, Q., Wang, X.: An improved potential field method for path planning. In Control and Decision Conference (CCDC), 2010 Chinese, pp 2265–2270 (2010)

  14. Kim, J. O., Khosla, P.: Real-time obstacle avoidance using harmonic potential functions. In IEEE Conference on Robotics and Automation, pp 790–796 (1991)

  15. Ahmad, A.: Masoud. A harmonic potential approach for simultaneous planning and control of a generic uav platform. J. Intell. Robot. Syst. 65(1-4), 153–173 (2012)

    Article  MATH  Google Scholar 

  16. Castillo, P., Lozano, R., Dzul, A.: Stabilization of a mini rotorcraft having four rotors. IEEE Control Syst. Mag. 25(6), 45–55 (2005)

    Article  MathSciNet  Google Scholar 

  17. García, L., Dzul, A., Santibáñez, V., Llama, M.: Quad-rotors formation based on potential functions with obstacle avoidance. IET Control Theory Aplications 6 (12), 1787–1802 (2012)

    Article  Google Scholar 

  18. Kim, D. H., Lee, H.-W., Shin, S., Suzuki, T.: Local path planning based on new repulsive potential functions with angle distributions. In Information Technology and Applications, 2005. ICITA 2005. Third Int. Conf. 2, 9–14 (2005)

    Google Scholar 

  19. Teel, A. R.: Global stabilization and restricted tracking for multiple integrators with bounded controls. Syst. Control Lett. 18, 165–171 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  20. Johnson, E. N., Kannan, S. K.: Nested saturation with guaranteed real poles. In American Control Conference, pp. 497–502, jun 4-6 (2003)

  21. Chen, C.-T., 3rd edition: Linear System Theory and Design, OUP USA (1998)

  22. García-Delgado, L., Gómez-Fuentes, R., García-Juárez, A., Leal Cruz, A. L., Berman-Mendoza, D., Vera-Marquina, A., Rojas-Hernndez, A. G.: An approach for optimal goal position assignment in vehicle formations. J. Intell. Robot. Syst. 73, 665–677 (2014)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to L. A. García-Delgado.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

García-Delgado, L.A., Noriega, J.R., Berman-Mendoza, D. et al. Repulsive Function in Potential Field Based Control with Algorithm for Safer Avoidance. J Intell Robot Syst 80, 59–70 (2015). https://doi.org/10.1007/s10846-014-0157-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-014-0157-z

Keywords

Navigation